Clean Water Issues, Community Behavior and Communication Models in Sustainable Development Goals 6 in Banten West Java Indonesia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Banten Province has four regencies and four cities, the city with the highest Regional Original Income is Tangerang City and the lowest is Serang City.The total population is 11.904.562people with the densest population occupied by Tangerang City as many as 1.895.486people while the area with the smallest population is Cilegon City with 434.896 people.The purpose of this study is to describe the data on the achievement of SDGs 6 in the Banten region as well as to find out the problems that occur in the implementation of the program.Qualitative method used in this research with the aim of integrating secondary data with qualitative data in order to produce a comprehensive picture.Secondary data was obtained from the report of the Indonesian Central Statistics Agency in 2022, while qualitative data was obtained through interviews and observations.The results of this study indicate that there are some differences in the achievement of SDGs 6; the problem of disparity in infrastructure development for SDGs 6 which causes infrastructure inequality in accessing clean water and implementing healthy environmental sanitation; economic inequality/poverty; problems of education and public knowledge are still weak and have an impact on the weak literacy of SDGs 6 as well; the weakness of community PHBS which is difficult to change.The participatory development communication model is a solution to the weak participation of stakeholders in achieving SDGS 6 in Banten Province.The recommendation resulting from this research to build synergy between various sectors.The implication of this research is the need for new policies to be made to foster public awareness about healthy lifestyles, policies on socialization, dissemination of information and management innovations, and environmental sustainability.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it